Systems and methods for optimizing diagnostics and therapeutics with metabolic profiling

ABSTRACT

The present disclosure is directed towards methods for calculating disease progression rates and sojourn times of solid tumors from metabolic markers and using this calculation to optimize patient-specific diagnosis, scheduling of screening procedures, and dosage or frequency of treatment.

FIELD OF THE DISCLOSURE

This disclosure relates to personalized medicine. More specifically,this disclosure relates to a method for optimizing diagnostics andtherapeutics of solid tumors with patient specific disease progressionrates and sojourn times using metabolic profiling in an exercisingsetup.

BACKGROUND

Current decision-making processes on scheduling of diagnostic andscreening procedures, or dosage and frequency regimes for therapeuticprocedures for Breast, Colon, Prostate, lung, and other solid tumors,are based on epidemiological data for patient categories discriminatedby age, genetic risk, family history, and few personal clinical featureswhich may limit the sensitivity of the screening apparatus, or theefficacy of the respective treatment.

One unknown in these decision-making processes is the patient-specificsojourn time of the disease in the phase to which the diagnostic ortherapeutic procedure is intended to apply. The sojourn time is afunction of the progression rate of the disease, and many of theseprocedures are optimal and most effective when synchronized with thisrate. Lack of appropriate methods to predict progression rates forindividual patients is the reason why sojourn times remain unknown. As aresult, patients are often treated with “one size fits all” strategy, inwhich the sojourn times are calculated via statistical averages from thepopulation. The best example for this strategy is the recentrecommendation from the US Preventive Service Task Force that all womenbetween 50 and 74 should go through biennial mammogram screening. Thisrecommendation may be optimal to some women, but will fail toearly-detect those with fast progression rate, and will lead tounnecessary stress and excess radiation in those with slow progressionrate.

Since the progression rates of solid tumors vary considerably betweendiagnosed patients, additional discriminatory measurements would haveprofound prognostic, diagnostic and therapeutic value, particularly forpersonalized medicine, and will ultimately lead to more informativediagnoses and more effective treatments and prognostics.

Contrary to global measures like BMI, which is mostly non-indicative forpersonalized medicine, the intracellular metabolic balance betweenoxidative phosphorylation, or OXPHOS (the production of ATP in themitochondria by burning Pyruvate with Oxygen) and Glycolysis (theproduction of ATP in the cytosol by the breakdown of Pyruvate to Lactatewithout Oxygen) strongly affects disease progression rates, directlythrough biosynthesis and indirectly through enhancement of immuneresponse, and thus provides a valuable personal diagnostic andtherapeutic discriminant for the above decision-making processes. Apossible context where this balance can become evident and measurable isaerobic exercise, where energy from aerobic and non-aerobic metabolismis concurrently produced in the skeletal muscles, yet while athletes usesome metabolic markers during aerobic exercise to customize theirtraining zones, so far there is no attempt to measure the intracellularmetabolic balance between OXPHOS and Glycolysis in vivo in humans.Current research in animal models does involve measurement of thismetabolic balance, but is directed solely at drug discovery, and not atpredicting patient-specific progression rates and sojourn times inanimals or in humans.

Thus, there remains a considerable need for methods that canconveniently predict patient-specific disease progression rates andsojourn times with metabolic markers, so that they can be incorporatedinto the current decision-making processes on prognostics, diagnosticsand therapeutics of solid tumors.

SUMMARY

Embodiments herein concerns methods for optimizing diagnostics, andtherapeutic procedures in a human patient, comprising the steps ofmeasuring the level of at least one metabolic marker in a patient, andcalculating disease progression rates and sojourn times, predicting atleast one incident selected from the group consisting of: diagnosis,timing of screening procedures, a type of treatment, a dosage oftreatment, and a frequency of treatment.

In some embodiments, methods for optimizing diagnostics, and therapeuticprocedures may include further the steps of providing the patient withan exercising equipment, allowing the patient to exercise on theexercising equipment for a period of time. Some embodiments may furtherinclude the step of adjusting an exercise level of the patient to thepatient's age and heart rate and/or the step of entering the measurementof the at least one metabolic marker to an algorithm.

In accordance with these embodiments, certain metabolic markers mayinclude, but not limited to, glucose, lactate, and pyruvate. In someembodiments, a patient may be fasted for at least 8 hour.

BRIEF DESCRIPTION OF THE DRAWINGS

The above mentioned and other features and objects of this disclosure,and the manner of attaining them, will become more apparent and thedisclosure itself will be better understood by reference to thefollowing description of exemplary embodiments of the disclosure takenin conjunction with the accompanying drawings, wherein:

FIG. 1A represents a possible embodiment of one of the two components ofthe measurement setup;

FIG. 1B represents a possible embodiment of the second of the twocomponents of the measurement setup;

FIG. 2 describes the Lactate clearance curve drawn from curve fittingthe 10 measurement points with a 3^(rd) degree polynomial (Cubic Spline)using standard curve fitting software;

FIG. 3. depicts the integral calculated by a standard curve fittingsoftware;

FIG. 4 depicts a possible embodiment of the computer interface allowingthe user to input the data from the measurement protocol (b) into the1^(st) algorithm in (c) that calculates the patient's metabolic score[MET];

FIG. 5 depicts the 2^(nd) algorithm in (c) for calculating the predictedgrowth rate (the doubling time, measured in days, [DT]) from thepatient's metabolic score [MET]; and

FIG. 6 depicts a possible embodiment of the computer interface for the3^(rd) algorithm in (c) that computes the sojourn time [DAYS] and thereceptive optimized frequency for a diagnostic procedure for a given[DT].

Corresponding reference characters indicate corresponding partsthroughout the several views. Although the drawings representembodiments of the present disclosure, the drawings are not necessarilyto scale and certain features may be exaggerated in order to betterillustrate and explain the present disclosure. The exemplification setout herein illustrates exemplary embodiments of the disclosure, invarious forms, and such exemplifications are not to be construed aslimiting the scope of the disclosure in any manner.

DETAILED DESCRIPTION

The embodiment disclosed below is not intended to be exhaustive or limitthe disclosure to the precise form disclosed in the following detaileddescription. Rather, the embodiments are chosen and described so thatothers skilled in the art may utilize its teachings.

One of ordinary skill in the art will realize that the embodimentsprovided can, be implemented in hardware, software, firmware, and/or acombination thereof. Programming code according to the embodiments canbe implemented in any viable programming language such as C, C++, HTML,XTML, JAVA or any other viable high-level programming language, or acombination of a high-level programming language and a lower levelprogramming language.

As used herein, the modifier “about” used in connection with a quantityis inclusive of the stated value and has the meaning dictated by thecontext (for example, it includes at least the degree of errorassociated with the measurement of the particular quantity). When usedin the context of a range, the modifier “about” should also beconsidered as disclosing the range defined by the absolute values of thetwo endpoints. For example, the range “from about 2 to about 4” alsodiscloses the range “from 2 to 4.”

Where a range of values is provided, it is understood that eachintervening value, to the tenth of the unit of the lower limit unlessthe context clearly dictates otherwise, between the upper and lowerlimit of that range and any other stated or intervening value in thatstated range is encompassed within the present disclosure. The upper andlower limits of these smaller ranges may independently be included inthe smaller ranges is also encompassed within the present disclosure,subject to any specifically excluded limit in the stated range. Wherethe stated range includes one or both of the limits, ranges excludingeither or both of those included limits are also included in the presentdisclosure.

Unless defined otherwise, all technical and scientific terms used hereinhave the same meaning as commonly understood by one of ordinary skill inthe art to which the present disclosure belongs. Although any methodsand materials similar or equivalent to those described herein can alsobe used in the practice or testing of the present disclosure, a limitednumber of the exemplary methods and materials are described herein.

It must be noted that as used herein and in the appended claims, thesingular forms “a”, “an”, and “the” include plural referents unless thecontext clearly dictates otherwise.

A therapeutically effective amount is an amount of a biologically activecompound that has a single or cumulative beneficial effect on the healthor well being of a patient.

The concept of measuring intracellular metabolic markers in humansduring exercise and, based on a functional relation between thesemarkers and sojourn times of solid tumors, using these markers tocalculate disease progression rates and sojourn times to optimizediagnostics and therapeutic procedures, customizing these procedures tothe individual patient.

Embodiments include a method for measuring metabolic markers in humansand calculating progression rates and sojourn times therefrom,comprising: (a) a measurement set up of (i) a reclined bike or atreadmill; (ii) Lactate and Glucose Analyzers; (iii) a human subjectfasting at least 8 hrs; (b) a measurement protocol comprising the stepsof: (i) 15 minutes of incremental aerobic exercise, adjusted to thesubject's age and Heart Rate at rest and calculated via Karvonen formula[(220−age−HRrest)*P %+HRrest], from P=50% through P=55%, P=60%, P=65%and up to P=70% of personal Maximal Heart Rate, spending 3 minutes ineach Heart Rate level, followed by 15 minutes of rest; (ii) measurementsof Lactate serum concentration at Minute 0, 3, 6, 9, 12, 15, 18, 21, 24,and 30; and (iii) measurements of average power output in Watt at Minute3, 6, 9, 12, and 15; (c) three algorithms.

Some embodiments may include a computer interface that allows enteringthe results from the measurement protocol (b) as input to the algorithmsfrom (c).

Some embodiments may include an algorithm from step (c) that takes as aninput the patient's age and the measurements in protocol (b)(ii-iii) andgives as an output the patient's metabolic score.

Some embodiments may include an algorithm that takes as input themetabolic score above and gives as an output the personal progressionrate of the disease (doubling time in days).

Some embodiments may include an Algorithm that takes as an input thepersonal progression rate above and yields as an output the sojourn timeof the disease between two designated time points of a particularclinical procedure, so that a schedule for a diagnostic procedure, or adosage and a frequency for a therapeutic procedure, can be calculatedbased on this sojourn time

In a preferred embodiment of the present disclosure, the measurementsetup described above involves a human subject who can independentlyperform the measurement protocol described above, either at home or atthe physician office, and subsequently receive recommendation forpersonal scheduling, dosage, or frequency of diagnostic or therapeuticprocedures, based on the personal sojourn time calculated from thesubject's metabolic score.

The present disclosure is designed so that the three algorithms that canbe implemented with data from the measurement protocol (b) either byusing the computer interface or by incorporating these algorithms ashardware into one or more components of the measurement setup in(a)(i-ii), so that the data from the setup will be automatically fedinto the concatenated chain of algorithms at the end of the protocol.

Various objects, features, aspects, and advantages of the presentdisclosure will become more apparent from the following detaileddescription of preferred embodiments of the present disclosure, alongwith the accompanying drawings in which like numerals represent likecomponents.

FIG. 1 represents a possible embodiment of two components of themeasurement setup ((a) and (b)).

FIG. 2 describes the Lactate clearance curve drawn from curve fittingthe 10 measurement points with a 3^(rd) degree polynomial (Cubic Spline)using standard commercial curve fitting software from. The data pointsare those obtained from using the apparatus in FIG. 1 on the humansubject who follows the measurement protocol (b).

FIG. 3 depicts the integral calculated by the Algorithm on that curve(the area below it) between point 0 (the initial time point of themeasurement protocol (b)) and point 30 (the final time point of themeasurement protocol in (b)).

FIG. 4 depicts a possible embodiment of the computer interface allowingthe user to input the data from the measurement protocol (b) into thefirst algorithm. This algorithm works as follows:

Algorithm I:

Step 1: Calculate the integral on the Lactate clearance curve (FIG. 6)in each 3 minutes interval between 0 and 15, and divide it by W/100,where W is the average Watt output, read from the apparatus in FIG. 1during each 3-minute segment, in 10 seconds intervals.

Step 2: Sum the 5 normalized area segments in Step 1.

Step 3: Calculate the integral on the Lactate clearance curve in theinterval between minute 15 and 30.

Step 4: Sum results from Step 2 and Step 3. This is the total normalizedarea [LAC]

Step 5: Calculate the age correction factor [Age] by subtracting 50 fromthe human subject current age. [Age] can be negative.

Step 6: Multiply result from Step 4 with

([Age]/100+1)

Step 7: Given the range of Lactate serum concentration in humans and thenature of the measurement protocol (b), the final result is a positivenumber between 0 and 3, designating the subject's metabolic score [MET].

FIG. 5 depicts the algorithm for calculating the predicted growth rate(the doubling time [DT], measured in days) from the subject's metabolicscore [MET]. The algorithm works as follows:

Algorithm II:

Step 1: Calculate the doubling time [DT] from the metabolic score [MET]given by Algorithm I (Step 7) using the formula:

[DT]=10{circumflex over ( )}(a−b*log₁₀[MET])

where the range of these parameters for a 95% confidence level (in thisparticular embodiment for Invasive Ductal Carcinoma) is.

a=3.53±0.11 and b=4.71±0.41

FIG. 6 depicts a possible embodiment of the computer interface for thealgorithm that computes the sojourn time for a given [DT]. In theexample presented here, a subject whose screening result is normal at agiven date can use the predicted progression rate [DT] to calculate thesojourn time of the disease under the assumption that the disease existsbut the screening apparatus failed to detect it because it is below orat the detection threshold. With this sojourn time the next schedule forscreening can be decided using the following steps:

Algorithm III:

Step 1: Calculate sojourn time [DAYS] with

[DAYS]=[DT]*(([RFN]*LOG₂([FN]/[T])÷[RTN]*LOG₂([TN))

Here [T] represents the threshold of detection of the screeningapparatus in mm³, ([T]=8 for digital mammography of breast tumor) andthe adjustable nominators in the LOG₂ ([FN] and [TN]) represent a targetvolume of the tumor in mm³ deemed appropriate for diagnostic purposes(in the embodiment in FIG. 6, [FN]=9 for the false negative case and[TN]=1 for the true negative case).

Thus the first part of the sum in each sojourn time(“([RFN]*LOG₂([FN]/[T])”) is calculated under the assumption that thecurrent normal mammogram is false negative and the tumor is at most atdetection threshold, and the second part of the sum in each sojourn time(“([RTN]*LOG₂([TN)”) is calculated under the assumption that the currentnormal mammogram is true negative but the tumor is below detectionthreshold, at 1 mm³.

The normalizing adjustable factors 0<[RFN]<1 and [RTN]=1−[RFN] representthe statistical rate of false and true negatives of the screeningapparatus, respectively (in the case of digital mammography for thisparticular embodiment, and according to the National Cancer Institute,[RFN] ranges between 10% and 20%).

The parameters [T] [FN] [TN] in Steps (1) of Algorithm III can beadjusted according to the specific disease, the sensitivity of thescreening apparatus for that disease, and the risk-aversion of thepatient.

Step 2: use [DAYS] to decide the optimal next screening date, now basedon the personal sojourn time and the sensitivity of the screeningapparatus, according to the following table (based on [RFN], [RTN],[FN], [TN] in the case of invasive ductal carcinoma):

-   -   If [DAYS]>730, next screening date is in 2 years    -   If [DAYS]<200 days, next screening date is in 6 months    -   If 200<[DAYS]<730, the next screening date is [DAYS] days from        current date

Since [DT] is calculated, using the personalized metabolic score [MET],the scheduling interval may differ from the average “one size fits all”recommendation. Embodiments ensure it will be customized to theindividual patient. This possible embodiment thus shows how thisdisclosure allows the physician and the subject to replace theprevailing decision making process on scheduling of screening which isbased on an “average” sojourn time in the population with a personalizeddecision making process which is customized to the individual subject.The benefit of this customized process is that subjects whose sojourntime is shorter than the average could now decide to schedule theirscreening frequency accordingly and would have a higher probability toearly detect the disease upon onset, while subjects whose sojourn timeis longer than the average could now decide to avoid unnecessary stressand excess radiation by scheduling their screening less frequently.

The reduction to practice of the disclosure to other types of solidtumors may require changes in the parameters (a,b) of Algorithm II, dueto known differences in cell growth in different tissues. The parameters[T] [FN] [TN] in Algorithm III will vary with the detection thresholdsand the false negative rates of the respective screening modality ineach disease, all this without changing any of the Independent orDependent Claims.

Thus, specific compositions and methods of optimizing diagnostics andtherapeutic schedules with metabolic profiling have been disclosed. Itshould be apparent, however, to those skilled in the art that many moremodifications besides those already described are possible withoutdeparting from the inventive concepts herein. The inventive subjectmatter, therefore, is not to be restricted except in the spirit of thedisclosure. Moreover, in interpreting the disclosure, all terms shouldbe interpreted in the broadest possible manner consistent with thecontext. In particular, the terms “comprises” and “comprising” should beinterpreted as referring to elements, components, or steps in anon-exclusive manner, indicating that the referenced elements,components, or steps may be present, or utilized, or combined with otherelements, components, or steps that are not expressly referenced.

While this disclosure has been described as having an exemplary design,the present disclosure may be further modified within the spirit andscope of this disclosure. This application is therefore intended tocover any variations, uses, or adaptations of the disclosure using itsgeneral principles. Further, this application is intended to cover suchdepartures from the present disclosure as come within known or customarypractice in the art to which this disclosure pertains.

Furthermore, the connecting lines shown in the various figures containedherein are intended to represent exemplary functional relationshipsand/or physical couplings between the various elements. It should benoted that many alternative or additional functional relationships orphysical connections may be present in a practical system. However, thebenefits, advantages, solutions to problems, and any elements that maycause any benefit, advantage, or solution to occur or become morepronounced are not to be construed as critical, required, or essentialfeatures or elements. The scope is accordingly to be limited by nothingother than the appended claims, in which reference to an element in thesingular is not intended to mean “one and only one” unless explicitly sostated, but rather “one or more.” Moreover, where a phrase similar to“at least one of A, B, or C” is used in the claims, it is intended thatthe phrase be interpreted to mean that A alone may be present in anembodiment, B alone may be present in an embodiment, C alone may bepresent in an embodiment, or that any combination of the elements A, Bor C may be present in a single embodiment; for example, A and B, A andC, B and C, or A and B and C.

In the detailed description herein, references to “one embodiment,” “anembodiment,” “an example embodiment,” etc., indicate that the embodimentdescribed may include a particular feature, structure, orcharacteristic, but every embodiment may not necessarily include theparticular feature, structure, or characteristic. Moreover, such phrasesare not necessarily referring to the same embodiment. Further, when aparticular feature, structure, or characteristic is described inconnection with an embodiment, it is submitted that it is within theknowledge of one skilled in the art with the benefit of the presentdisclosure to affect such feature, structure, or characteristic inconnection with other embodiments whether or not explicitly described.After reading the description, it will be apparent to one skilled in therelevant art(s) how to implement the disclosure in alternativeembodiments.

Furthermore, no element, component, or method step in the presentdisclosure is intended to be dedicated to the public regardless ofwhether the element, component, or method step is explicitly recited inthe claims. No claim element herein is to be construed under theprovisions of 35 U.S.C. § 112(f), unless the element is expresslyrecited using the phrase “means for.” As used herein, the terms“comprises,” “comprising,” or any other variation thereof, are intendedto cover a non-exclusive inclusion, such that a process, method,article, or apparatus that comprises a list of elements does not includeonly those elements but may include other elements not expressly listedor inherent to such process, method, article, or apparatus.

What is claimed is:
 1. (canceled)
 2. (canceled)
 3. (canceled) 4.(canceled)
 5. (canceled)
 6. (canceled)
 7. (canceled)
 8. (canceled)
 9. Amethod for optimizing diagnostics and therapeutic procedures for solidtumors in a human patient by measuring metabolic markers duringexercise, the method comprising the steps of: measuring the level of atleast one metabolic marker in a patient during exercise; and calculatingdisease progression rates and sojourn times based on a functionalrelation between at least one metabolic marker and disease progressionrates and sojourn time; predicting at least one incident selected fromthe group consisting of: diagnosis, timing of screening procedures, atype of treatment, a dosage of treatment, a timing of treatment, and afrequency of treatment.
 10. The method of claim 1, further comprisingthe steps of: providing the patient with an exercising equipment;allowing the patient to exercise on the exercising equipment for aperiod of time.
 11. The method of claim 2, further comprising the stepof adjusting an exercise level of the patient to the patient's age andheart rate.
 12. The method of claim 1, further comprising the step ofentering the measurement of the at least one metabolic marker to analgorithm.
 13. The method of claim 1, wherein the at least one metabolicmarker comprises of glucose, lactate, or pyruvate.
 14. The method ofclaim 1, wherein the patient has been fasting for at least 8 hours. 15.The method of claim 1, wherein the measurement is done by a finger stickblood draw, sweat draw or saliva draw.
 16. The method of claim 1,wherein the optimization of the timing and frequency of screening ordiagnostics procedures, or the dosage, timing and frequency oftreatment, or the dosage, timing and frequency of a therapeuticprocedure is done with an algorithm that calculates the patient'smetabolic score from the measured metabolic marker; then calculates thepotential progression rate and sojourn time from the patient's metabolicscore; then uses the calculated progression rate and sojourn time tocalculate the personalized timing and frequency of screening ordiagnostics procedures, or the personalized dosage, timing and frequencyof treatment, or the personalized dosage, timing and frequency of atherapeutic procedure.